12 February 2001 Cellular neural networks and biologically inspired motion control
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Proceedings Volume 4190, Optomechatronic Systems; (2001) https://doi.org/10.1117/12.417229
Event: Intelligent Systems and Smart Manufacturing, 2000, Boston, MA, United States
Abstract
12 The main purpose of this paper is to present the Cellular Neural Network (CNN) Paradigm as a powerful strategy to design and to implement in hardware efficient locomotion control techniques. A gallery of biologically inspired walking robots are presented. Moreover, the availability of efficient distributed control structures needs a sensing capability of the same efficiency. Therefore the sensing stage is performed by using once again the CNN paradigm, but used as fast image processors. The strategy is supported by the fact that CNN devices with on-chip optical sensors are currently being tested and will be soon available. In such a way, images are acquired by a video camera with a CNN image processing device, able to extract the key features. These ones represent the `command' to take on the right locomotion pattern. Since all the methodology is realized by using analog processors, the whole strategy represents a real breakthrough in the smart sensing and control field.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Paolo Arena, Luigi Fortuna, "Cellular neural networks and biologically inspired motion control", Proc. SPIE 4190, Optomechatronic Systems, (12 February 2001); doi: 10.1117/12.417229; https://doi.org/10.1117/12.417229
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